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Source channel @githubtrending · Post #15271 · Nov 5

#cplusplus#arm#baidu#deep_learning#embedded#fpga#mali#mdl#mobile#mobile_deep_learning#neural_network Paddle Lite is a lightweight, high-performance deep learning inference framework designed to run AI models efficiently on mobile, embedded, and edge devices. It supports multiple platforms like Android, iOS, Linux, Windows, and macOS, and languages including C++, Java, and Python. You can easily convert models from other frameworks to PaddlePaddle format, optimize them for faster and smaller deployment, and run them with ready-made examples. This helps you deploy AI applications quickly on various devices with low memory use and fast speed, making it ideal for real-time, resource-limited environments. It also supports many hardware accelerators for better performance. https://github.com/PaddlePaddle/Paddle-Lite

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Crypto M - Crypto News

@CryptoM · Post #65294 · 04/12/2026, 03:15 PM

🚀 TRON Network Implements Proposal 106 to Enhance Compatibility TRON Network has officially passed Proposal 106 as of April 10 at 20:00 UTC+8. According to ChainCatcher, the mainnet has adjusted the behavior and execution cost of the SELFDESTRUCT instruction. Contracts will only be permanently removed from the blockchain if the instruction is called within the same transaction as the contract's creation. Otherwise, executing the instruction will merely transfer the assets within the contract to a specified address, without deleting the contract itself. Additionally, the energy consumption for SELFDESTRUCT has been changed from 0 to 5000. This adjustment aligns TRON's mechanisms more closely with Ethereum, enhancing the compatibility of the TRON Virtual Machine (TVM). It aims to provide more stable foundational support for multi-chain development and ecosystem adaptation. #TRON#Proposal106#Blockchain#Ethereum#TVM#SELFDESTRUCT#Mainnet#MultiChain#Ecosystem#Crypto#ETH#TRX